1. Field of the Invention
The present invention relates to a device and method for coding/decoding gray scale shape data and, more particularly, to a gray scale shape data encoder/decoder which divides a boundary macro block into sub-blocks and merges/splits each of the sub-blocks with respect to the proximity in length and the correlation, thereby encoding/decoding gray scale shape data.
2. Discussion of Related Art
In synthesizing multitude of images, each screen has luminance, chrominance and shape data. The shape data comprises binary shape data for representing a profile of an object, and transparency data for representing the weight of each of the pixels forming the screen.
An image is split into a grid of 16.times.16 macro blocks. Therefore, the split blocks are rearranged to code the image as illustrated in FIG. 1. The image is divided into a region having no object image data and other region having the object image data. The region is split into macro blocks 13 having only image data(hereinafter, it is referred to as an interior macro block), a macro block 11 having no object image data (hereinafter, it is referred to as an exterior macro block), and another macro block 15 consisting of a region having the object image data and another region having no object image data (hereinafter, it is referred to as a boundary macro block).
One macro block, as illustrated in FIG. 2, is coded by splitting it into luminance sub-blocks B1 to B4, two chrominance signal sub-blocks B5 and B6, and four shape data sub-blocks B7 to B10.
The luminance block of the boundary macro block 15, as illustrated in FIG. 3, is split into 8.times.8 sub-blocks: a sub-block 31 having only image data(hereinafter, it is referred to as an interior sub-block), a sub-block 33 having no object image data(hereinafter, it is referred to as an exterior sub-block), and another sub-block 32 consisting of a region having the object image data and another region having no object image data (hereinafter, it is referred to as a boundary sub-block). In a method of encoding image data of the object made of the above sub-blocks, the exterior sub-block and the exterior macro block in the boundary macro block are not coded, while the interior sub-block and the interior macro block in the boundary macro block are coded by using a discrete cosine transform (DCT) or a shape adaptive DCT (SADCT).
But with the conventional method of encoding image data in an object, the quality of the image is inversely proportional to a bit ratio reducing efficiency. In other words, if the quality of the image is improved, the bit ratio reducing efficiency is decreased and vice versa. Therefore, there has been provided an encoding/decoding method of merging adjacent boundary sub-blocks into one block, thereby minimizing the decrease of the quality of the image while reducing the bit ratio of the coded bit as well as maintaining and enhancing the quality of the image.
As described above, the boundary block merging/splitting technique is applied to only luminance blocks of the boundary macro block and finally coding/decoding the block, so that the technique can maintain or enhance the quality of image without drastically decreasing the quality of the image, and reducing coded bits of the image data, gaining high coding/decoding efficiency.
Gray scale shape data are to be applied to an image synthesis, originally for representing an object region and its transparency. But for coding, the gray scale shape data is to be split into the binary shape data for representing the object region and the transparency data made of the transparency value as in FIG. 4. A supporting means 42 receives gray scale shape data 41, and extracts and outputs the binary data. The binary shape data output from the support means 42 are input to the binary shape data coding means 43. A transparency data extracting means 44 receives the gray scale shape data, and extracts and outputs the transparency data. The transparency data coding means 45 receives the transparency data output from the transparency data extracting means 44 and codes the transparency data by using a content-based texture coding technique as discussed below.
But, when the conventional content-based texture coding technique is applied to coding the transparency data of the gray scale shape data, the quality of image is still inversely proportional to the bit ratio reducing effect. Therefore, if the quality of image is improved, the bit ratio reducing effect is decreased and vice versa.